cgevans / scikits-bootstrapLinks
Python/numpy bootstrap confidence interval estimation.
☆179Updated 3 months ago
Alternatives and similar repositories for scikits-bootstrap
Users that are interested in scikits-bootstrap are comparing it to the libraries listed below
Sorting:
- ☆159Updated 3 years ago
- Bayesian estimation supersedes the t test☆145Updated 3 years ago
- Decorator for PyMC3☆50Updated 4 years ago
- Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/pre…☆127Updated 9 years ago
- Patsy Adaptors for Scikit-learn☆48Updated 6 years ago
- Conventionally parameterized probability distributions☆35Updated last year
- PyMC Example Notebooks☆74Updated 11 years ago
- Efficient pure Python implementation of Friedman's Supersmoother☆99Updated 2 months ago
- bayesian bootstrapping in python☆123Updated 3 years ago
- Generalized linear mixed-effect model in Python☆182Updated 7 years ago
- Python implementation of elastic-net regularized generalized linear models☆286Updated 2 years ago
- Collection of jupyter notebooks for demonstrating software.☆169Updated 2 years ago
- Generalized Linear Models in Sklearn Style☆130Updated 5 years ago
- PCA that iteratively replaces missing data☆222Updated last year
- Confidence intervals for scikit-learn forest algorithms☆290Updated 7 months ago
- PyMC3 tutorial for DataScience LA (January 2017)☆67Updated 7 years ago
- A python port of the glmnet package for fitting generalized linear models via penalized maximum likelihood.☆269Updated last year
- Probabilistic programming in Python workshop at Oslo universitetssykehus HF☆36Updated 9 years ago
- A Python package for Approximate Bayesian Computation☆38Updated 9 years ago
- Scikit-learn compatible estimation of general graphical models☆247Updated 5 months ago
- Implementation of Hidden Markov Models in pymc3☆62Updated 8 years ago
- A library of scalable Bayesian generalised linear models with fancy features☆60Updated 8 years ago
- A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.☆213Updated 8 years ago
- PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course☆96Updated 8 years ago
- pymc-learn: Practical probabilistic machine learning in Python☆232Updated 4 years ago
- ☆99Updated 7 years ago
- Teaching materials for Python MixedLM (mixed linear models)☆48Updated 8 years ago
- Multiple correspondence analysis☆181Updated last week
- Python solver for mixed-effects models☆97Updated 6 months ago
- A garden for scikit-learn compatible trees☆288Updated last year